index int64 0 20.3k | text stringlengths 0 1.3M | year stringdate 1987-01-01 00:00:00 2024-01-01 00:00:00 | No stringlengths 1 4 |
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3,400 | Optimization on a Budget: A Reinforcement Learning Approach Paul Ruvolo Department of Computer Science University of California San Diego La Jolla, CA 92093 pruvolo@cs.ucsd.edu Ian Fasel Department of Computer Sciences University of Texas at Austin ianfasel@cs.utexas.edu Javier Movellan Machine ... | 2008 | 152 |
3,401 | Dependent Dirichlet Process Spike Sorting Jan Gasthaus, Frank Wood, Dilan G¨or¨ur, Yee Whye Teh Gatsby Computational Neuroscience Unit University College London London, WC1N 3AR, UK {j.gasthaus, fwood, dilan, ywteh}@gatsby.ucl.ac.uk Abstract In this paper we propose a new incremental spike sorting model t... | 2008 | 153 |
3,402 | The Recurrent Temporal Restricted Boltzmann Machine Ilya Sutskever, Geoffrey Hinton, and Graham Taylor University of Toronto {ilya, hinton, gwtaylor}@cs.utoronto.ca Abstract The Temporal Restricted Boltzmann Machine (TRBM) is a probabilistic model for sequences that is able to successfully model (i.e., ge... | 2008 | 154 |
3,403 | Short-Term Depression in VLSI Stochastic Synapse Peng Xu, Timothy K. Horiuchi, and Pamela Abshire Department of Electrical and Computer Engineering, Institute for Systems Research University of Maryland, College Park, MD 20742 pxu,timmer,pabshire@umd.edu Abstract We report a compact realization of short-ter... | 2008 | 155 |
3,404 | Generative and Discriminative Learning with Unknown Labeling Bias Miroslav Dud´ık Carnegie Mellon University 5000 Forbes Ave, Pittsburgh, PA 15213 mdudik@cmu.edu Steven J. Phillips AT&T Labs −Research 180 Park Ave, Florham Park, NJ 07932 phillips@research.att.com Abstract We apply robust Bayesian ... | 2008 | 156 |
3,405 | Large Margin Taxonomy Embedding with an Application to Document Categorization Kilian Weinberger Yahoo! Research kilian@yahoo-inc.com Olivier Chapelle Yahoo! Research chap@yahoo-inc.com Abstract Applications of multi-class classification, such as document categorization, often appear in cost-sensitiv... | 2008 | 157 |
3,406 | Modeling the effects of memory on human online sentence processing with particle filters Roger Levy Department of Linguistics University of California, San Diego rlevy@ling.ucsd.edu Florencia Reali Thomas L. Griffiths Department of Psychology University of California, Berkeley {floreali,tom griffiths}... | 2008 | 158 |
3,407 | Clusters and Coarse Partitions in LP Relaxations David Sontag CSAIL, MIT dsontag@csail.mit.edu Amir Globerson School of Computer Science and Engineering The Hebrew University gamir@cs.huji.ac.il Tommi Jaakkola CSAIL, MIT tommi@csail.mit.edu Abstract We propose a new class of consistency constrai... | 2008 | 159 |
3,408 | Unifying the Sensory and Motor Components of Sensorimotor Adaptation Adrian Haith School of Informatics University of Edinburgh, UK adrian.haith@ed.ac.uk Carl Jackson School of Psychology University of Birmingham, UK c.p.jackson.1@bham.ac.uk Chris Miall School of Psychology University of Birming... | 2008 | 16 |
3,409 | Bounds on marginal probability distributions Joris Mooij MPI for Biological Cybernetics T¨ubingen, Germany joris.mooij@tuebingen.mpg.de Bert Kappen Department of Biophysics Radboud University Nijmegen, the Netherlands b.kappen@science.ru.nl Abstract We propose a novel bound on single-variable margin... | 2008 | 160 |
3,410 | Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation Indraneel Mukherjee David M. Blei Department of Computer Science Princeton University 35 Olden Street Princeton, NJ 08540 {imukherj,blei}@cs.princeton.edu Abstract Hierarchical probabilistic modeling of discrete... | 2008 | 161 |
3,411 | Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning Francis Bach INRIA - Willow Project, ´Ecole Normale Sup´erieure 45, rue d’Ulm, 75230 Paris, France francis.bach@mines.org Abstract For supervised and unsupervised learning, positive definite kernels allow to use large and potential... | 2008 | 162 |
3,412 | MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features Tae-Kyun Kim∗ Sidney Sussex College University of Cambridge Cambridge CB2 3HU, UK tkk22@cam.ac.uk Roberto Cipolla Department of Engineering University of Cambridge Cambridge CB2 1PZ, UK cipolla@cam.ac.u... | 2008 | 163 |
3,413 | Load and Attentional Bayes Peter Dayan Gatsby Computational Neuroscience Unit, UCL London, England, WC1N 3AR dayan@gatsby.ucl.ac.uk Abstract Selective attention is a most intensively studied psychological phenomenon, rife with theoretical suggestions and schisms. A critical idea is that of limited capacit... | 2008 | 164 |
3,414 | Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 Klaus Wimmer1*, Marcel Stimberg1*, Robert Martin1, Lars Schwabe2, Jorge Mariño3, James Schummers4, David C. Lyon5, Mriganka Sur4, and Klaus Obermayer1 1 Bernstein Center for Computational Neuroscience and Technische... | 2008 | 165 |
3,415 | An interior-point stochastic approximation method and an L1-regularized delta rule Peter Carbonetto pcarbo@cs.ubc.ca Mark Schmidt schmidtm@cs.ubc.ca Nando de Freitas nando@cs.ubc.ca Department of Computer Science University of British Columbia Vancouver, B.C., Canada V6T 1Z4 Abstract The stochas... | 2008 | 166 |
3,416 | Dynamic Visual Attention: Searching for coding length increments Xiaodi Hou1,2 and Liqing Zhang1 ∗ 1Department of Computer Science and Engineering, Shanghai Jiao Tong University No. 800 Dongchuan Road, 200240, China 2Department of Computation and Neural Systems, California Institute of Technology MC 136-93,... | 2008 | 167 |
3,417 | Joint support recovery under high-dimensional scaling: Benefits and perils of ℓ1,∞-regularization Sahand Negahban Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA 94720-1770 sahand n@eecs.berkeley.edu Martin J. Wainwright Department of Statistics,... | 2008 | 168 |
3,418 | Online Metric Learning and Fast Similarity Search Prateek Jain, Brian Kulis, Inderjit S. Dhillon, and Kristen Grauman Department of Computer Sciences University of Texas at Austin Austin, TX 78712 {pjain,kulis,inderjit,grauman}@cs.utexas.edu Abstract Metric learning algorithms can provide useful distance ... | 2008 | 169 |
3,419 | Modeling human function learning with Gaussian processes Thomas L. Griffiths Christopher G. Lucas Joseph J. Williams Department of Psychology University of California, Berkeley Berkeley, CA 94720-1650 {tom griffiths,clucas,joseph williams}@berkeley.edu Michael L. Kalish Institute of Cognitive Science U... | 2008 | 17 |
3,420 | Bayesian Network Score Approximation using a Metagraph Kernel Benjamin Yackley Department of Computer Science University of New Mexico Eduardo Corona Courant Institute of Mathematical Sciences New York University Terran Lane Department of Computer Science University of New Mexico Abstract Many i... | 2008 | 170 |
3,421 | Fast Rates for Regularized Objectives Karthik Sridharan, Nathan Srebro, Shai Shalev-Shwartz Toyota Technological Institute — Chicago Abstract We study convergence properties of empirical minimization of a stochastic strongly convex objective, where the stochastic component is linear. We show that the value ... | 2008 | 171 |
3,422 | Bayesian Synchronous Grammar Induction Phil Blunsom, Trevor Cohn, Miles Osborne School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh, EH8 9AB, UK {pblunsom,tcohn,miles}@inf.ed.ac.uk Abstract We present a novel method for inducing synchronous context free grammars (SCFGs) from a cor... | 2008 | 172 |
3,423 | Tracking Changing Stimuli in Continuous Attractor Neural Networks C. C. Alan Fung, K. Y. Michael Wong Department of Physics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China alanfung@ust.hk, phkywong@ust.hk Si Wu Department of Informatics, University of Sussex, Brighto... | 2008 | 173 |
3,424 | Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity Byron M. Yu1,2,4, John P. Cunningham1, Gopal Santhanam1, Stephen I. Ryu1,3, Krishna V. Shenoy1,2 1Department of Electrical Engineering, 2Neurosciences Program, 3Department of Neurosurgery, Stanford Univers... | 2008 | 174 |
3,425 | Kernel Measures of Independence for non-iid Data Xinhua Zhang NICTA and Australian National University Canberra, Australia xinhua.zhang@anu.edu.au Le Song∗ School of Computer Science Carnegie Mellon University, Pittsburgh, USA lesong@cs.cmu.edu Arthur Gretton MPI T¨ubingen for Biological Cybernetics... | 2008 | 175 |
3,426 | Regularized Policy Iteration Amir-massoud Farahmand1, Mohammad Ghavamzadeh2, Csaba Szepesv´ari1, Shie Mannor3 ∗ 1Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada 2INRIA Lille - Nord Europe, Team SequeL, France 3Department of ECE, McGill University, Canada - Department of EE, Tec... | 2008 | 176 |
3,427 | Dimensionality Reduction for Data in Multiple Feature Representations Yen-Yu Lin1,2 Tyng-Luh Liu1 Chiou-Shann Fuh2 1Institute of Information Science, Academia Sinica, Taipei, Taiwan {yylin, liutyng}@iis.sinica.edu.tw 2Department of CSIE, National Taiwan University, Taipei, Taiwan fuh@csie.ntu.edu.tw A... | 2008 | 177 |
3,428 | Continuously-adaptive discretization for message-passing algorithms Kannan Achan Microsoft Research Silicon Valley Mountain View, California, USA Michael Isard Microsoft Research Silicon Valley Mountain View, California, USA John MacCormick Dickinson College Carlisle, Pennsylvania, USA Abstract ... | 2008 | 178 |
3,429 | On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing Benjamin Schrauwen Electronics and Information Systems Department Ghent University B-9000 Ghent, Belgium benjamin.schrauwen@ugent.be Lars B¨using, Robert Legenstein Institute for Theoretical Computer Science Graz Univer... | 2008 | 179 |
3,430 | Hebbian Learning of Bayes Optimal Decisions Bernhard Nessler∗, Michael Pfeiffer∗, and Wolfgang Maass Institute for Theoretical Computer Science Graz University of Technology A-8010 Graz, Austria {nessler,pfeiffer,maass}@igi.tugraz.at Abstract Uncertainty is omnipresent when we perceive or interact with ou... | 2008 | 18 |
3,431 | Mind the Duality Gap: Logarithmic regret algorithms for online optimization Sham M. Kakade Toyota Technological Institute at Chicago sham@tti-c.org Shai Shalev-Shwartz Toyota Technological Institute at Chicago shai@tti-c.org Abstract We describe a primal-dual framework for the design and analysis of o... | 2008 | 180 |
3,432 | Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data Tran The Truyen †, Dinh Q. Phung †, Hung H. Bui ‡∗, and Svetha Venkatesh † †Department of Computing, Curtin University of Technology GPO Box U1987 Perth, WA 6845, Australia thetruyen.tran@postgrad.curtin.edu.au {D.Phung,S.Venka... | 2008 | 181 |
3,433 | A spatially varying two-sample recombinant coalescent, with applications to HIV escape response Alexander Braunstein Statistics Department University of Pennsylvania Wharton School Philadelphia, PA 19104 braunsf@wharton.upenn.edu Zhi Wei Computer Science Department New Jersey Institute of Technology... | 2008 | 182 |
3,434 | Measures of Clustering Quality: A Working Set of Axioms for Clustering Margareta Ackerman and Shai Ben-David School of Computer Science University of Waterloo, Canada Abstract Aiming towards the development of a general clustering theory, we discuss abstract axiomatization for clustering. In this respect, w... | 2008 | 183 |
3,435 | Structure Learning in Human Sequential Decision-Making Daniel Acu˜na Dept. of Computer Science and Eng. University of Minnesota–Twin Cities acuna002@umn.edu Paul Schrater Dept. of Psychology and Computer Science and Eng. University of Minnesota–Twin Cities schrater@umn.edu Abstract We use graphica... | 2008 | 184 |
3,436 | Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance Jeremy Hill1 Jason Farquhar2 Suzanne Martens1 Felix Bießmann1,3 Bernhard Sch¨olkopf1 1Max Planck Institute for Biological Cybernetics {firstname.lastname}@tuebingen.mpg.de 2NICI, Radboud University, Nijmegen, The N... | 2008 | 185 |
3,437 | Supervised Dictionary Learning Julien Mairal INRIA-Willow project julien.mairal@inria.fr Francis Bach INRIA-Willow project francis.bach@inria.fr Jean Ponce Ecole Normale Sup´erieure jean.ponce@ens.fr Guillermo Sapiro University of Minnesota guille@ece.umn.edu Andrew Zisserman University of O... | 2008 | 186 |
3,438 | Natural Image Denoising with Convolutional Networks Viren Jain1 1Brain & Cognitive Sciences Massachusetts Institute of Technology H. Sebastian Seung1,2 2Howard Hughes Medical Institute Massachusetts Institute of Technology Abstract We present an approach to low-level vision that combines two main idea... | 2008 | 187 |
3,439 | Optimal Response Initiation: Why Recent Experience Matters Matt Jones Dept. of Psychology & Institute of Cognitive Science University of Colorado mcj@colorado.edu Michael C. Mozer Dept. of Computer Science & Institute of Cognitive Science University of Colorado mozer@colorado.edu Sachiko Kinoshi... | 2008 | 188 |
3,440 | Bayesian Experimental Design of Magnetic Resonance Imaging Sequences Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann and Bernhard Sch¨olkopf Max Planck Institute for Biological Cybernetics Spemannstraße 38 72012 T¨ubingen, Germany {seeger,hn,rolf.pohmann,bs}@tuebingen.mpg.de Abstract We show how impro... | 2008 | 189 |
3,441 | An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis Gabriele Schweikert1 Max Planck Institutes Spemannstr. 35-39, 72070 T¨ubingen, Germany Gabriele.Schweikert@tue.mpg.de Christian Widmer1 Friedrich Miescher Laboratory Spemannstr. 39, 72070 T¨ubingen, Germany ZBIT, T¨ubi... | 2008 | 19 |
3,442 | Temporal Dynamics of Cognitive Control Jeremy R. Reynolds Department of Psychology University of Denver Denver, CO 80208 jeremy.reynolds@psy.du.edu Michael C. Mozer Department of Computer Science and Institute of Cognitive Science University of Colorado Boulder, CO 80309 mozer@colorado.edu Abstr... | 2008 | 190 |
3,443 | Overlaying classifiers: a practical approach for optimal ranking St´ephan Cl´emenc¸on Telecom Paristech (TSI) - LTCI UMR Institut Telecom/CNRS 5141 stephan.clemencon@telecom-paristech.fr Nicolas Vayatis ENS Cachan & UniverSud - CMLA UMR CNRS 8536 vayatis@cmla.ens-cachan.fr Abstract ROC curves are one o... | 2008 | 191 |
3,444 | Model selection and velocity estimation using novel priors for motion patterns Shuang Wu Department of Statistics UCLA, Los Angeles, CA 90095 shuangw@stat.ucla.edu Hongjing Lu Department of Psychology UCLA, Los Angeles, CA 90095 hongjing@ucla.edu Alan Yuille Department of Statistics UCLA Los A... | 2008 | 192 |
3,445 | Estimation of Information Theoretic Measures for Continuous Random Variables Fernando P´erez-Cruz Princeton University, Electrical Engineering Department B-311 Engineering Quadrangle, 08544 Princeton (NJ) fp@princeton.edu Abstract We analyze the estimation of information theoretic measures of continuous r... | 2008 | 193 |
3,446 | On the Reliability of Clustering Stability in the Large Sample Regime - Supplementary Material Ohad Shamir† and Naftali Tishby†‡ † School of Computer Science and Engineering ‡ Interdisciplinary Center for Neural Computation The Hebrew University Jerusalem 91904, Israel {ohadsh,tishby}@cs.huji.ac.il A ... | 2008 | 194 |
3,447 | Using matrices to model symbolic relationships Ilya Sutskever and Geoffrey Hinton University of Toronto {ilya, hinton}@cs.utoronto.ca Abstract We describe a way of learning matrix representations of objects and relationships. The goal of learning is to allow multiplication of matrices to represent symbolic ... | 2008 | 195 |
3,448 | Psychiatry: insights into depression through normative decision-making models Quentin JM Huys1,2,∗Joshua T Vogelstein3,∗and Peter Dayan2,∗ 1Center for Theoretical Neuroscience, Columbia University, New York, NY 10032, USA 2Gatsby Computational Neuroscience Unit, University College London, London, WC1N 3AR, UK ... | 2008 | 196 |
3,449 | Characteristic Kernels on Groups and Semigroups Kenji Fukumizu Institute of Statistical Mathematics 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106-8569 Japan fukumizu@ism.ac.jp Bharath Sriperumbudur Department of ECE, UC San Diego / MPI for Biological Cybernetics bharathsv@ucsd.edu Arthur Gretton MPI for ... | 2008 | 197 |
3,450 | Multi-label Multiple Kernel Learning Shuiwang Ji Arizona State University Tempe, AZ 85287 shuiwang.ji@asu.edu Liang Sun Arizona State University Tempe, AZ 85287 sun.liang@asu.edu Rong Jin Michigan State University East Lansing, MI 48824 rongjin@cse.msu.edu Jieping Ye Arizona State University... | 2008 | 198 |
3,451 | Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl Juan Huo, Zhijun Yang and Alan Murray DTC, School of Informatics, Schoolf of Electronics & Engineering The University of Edinburgh Edinburgh, UK {J.Huo, Zhijun.Yang, Alan.Murray}@ed.ac.uk Abstract The visual and auditory map alignment ... | 2008 | 199 |
3,452 | Translated Learning: Transfer Learning across Different Feature Spaces †Wenyuan Dai, †Yuqiang Chen, †Gui-Rong Xue, ‡Qiang Yang and †Yong Yu †Shanghai Jiao Tong University Shanghai 200240, China {dwyak,yuqiangchen,grxue,yyu}@apex.sjtu.edu.cn ‡Hong Kong University of Science and Technology Kowloon, Hong Kon... | 2008 | 2 |
3,453 | Kernel Change-point Analysis Za¨ıd Harchaoui LTCI, TELECOM ParisTech and CNRS 46, rue Barrault, 75634 Paris cedex 13, France zaid.harchaoui@enst.fr Francis Bach Willow Project, INRIA-ENS 45, rue d’Ulm, 75230 Paris, France francis.bach@mines.org ´Eric Moulines LTCI, TELECOM ParisTech and CNRS 46, r... | 2008 | 20 |
3,454 | Spectral Hashing Yair Weiss1,3 3School of Computer Science, Hebrew University, 91904, Jerusalem, Israel yweiss@cs.huji.ac.il Antonio Torralba1 1CSAIL, MIT, 32 Vassar St., Cambridge, MA 02139 torralba@csail.mit.edu Rob Fergus2 2Courant Institute, NYU, 715 Broadway, New York, NY 10003 fergus... | 2008 | 200 |
3,455 | Multi-resolution Exploration in Continuous Spaces Ali Nouri Department of Computer Science Rutgers University Piscataway , NJ 08854 nouri@cs.rutgers.edu Michael L. Littman Department of Computer Science Rutgers University Piscataway , NJ 08854 mlittman@cs.rutgers.edu Abstract The essence of expl... | 2008 | 201 |
3,456 | A computational model of hippocampal function in trace conditioning Elliot A. Ludvig, Richard S. Sutton, Eric Verbeek Department of Computing Science University of Alberta Edmonton, AB, Canada T6G 2E8 {elliot,sutton,everbeek}@cs.ualberta.ca E. James Kehoe School of Psychology University of New South W... | 2008 | 202 |
3,457 | Online Prediction on Large Diameter Graphs Mark Herbster, Guy Lever, Massimiliano Pontil Department of Computer Science University College London Gower Street, London WC1E 6BT, England, UK {m.herbster, g.lever, m.pontil}@cs.ucl.ac.uk Abstract We continue our study of online prediction of the labelling... | 2008 | 203 |
3,458 | Sparse probabilistic projections C´edric Archambeau Department of Computer Science University College London, United Kingdom c.archambeau@cs.ucl.ac.uk Francis R. Bach INRIA - Willow Project Ecole Normale Sup´erieure, Paris, France francis.bach@mines.org Abstract We present a generative model for per... | 2008 | 204 |
3,459 | Sparsity of SVMs that use the ϵ-insensitive loss Ingo Steinwart Information Sciences Group CCS-3 Los Alamos National Laboratory Los Alamos, NM 87545, USA ingo@lanl.gov Andreas Christmann University of Bayreuth Department of Mathematics D-95440 Bayreuth Andreas.Christmann@uni-bayreuth.de Abstract ... | 2008 | 205 |
3,460 | Automatic online tuning for fast Gaussian summation Vlad I. Morariu1∗, Balaji V. Srinivasan1, Vikas C. Raykar2, Ramani Duraiswami1, and Larry S. Davis1 1University of Maryland, College Park, MD 20742 2Siemens Medical Solutions Inc., USA, 912 Monroe Blvd, King of Prussia, PA 19406 morariu@umd.edu, balajiv@umiacs... | 2008 | 206 |
3,461 | Reducing statistical dependencies in natural signals using radial Gaussianization Siwei Lyu Computer Science Department University at Albany, SUNY Albany, NY 12222 lsw@cs.albany.edu Eero P. Simoncelli Center for Neural Science New York University New York, NY 10003 eero@cns.nyu.edu Abstract We... | 2008 | 207 |
3,462 | A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning Massih R. Amini Laboratoire d’Informatique de Paris 6 Universit´e Pierre et Marie Curie, Paris, France massih-reza.amini@lip6.fr Franc¸ois Laviolette Universit´e Laval Qu´ebec (QC), Canada francois.laviolette@... | 2008 | 208 |
3,463 | Nonrigid Structure from Motion in Trajectory Space Ijaz Akhter LUMS School of Science and Engineering Lahore, Pakistan akhter@lums.edu.pk Yaser Sheikh Carnegie Mellon University Pittsburgh, PA, USA yaser@cs.cmu.edu Sohaib Khan LUMS School of Science and Engineering Lahore, Pakistan sohaib@lums.e... | 2008 | 209 |
3,464 | Biasing Approximate Dynamic Programming with a Lower Discount Factor Marek Petrik Department of Computer Science University of Massachusetts Amherst Amherst, MA 01003 petrik@cs.umass.edu Bruno Scherrer LORIA Campus Scientifique B.P. 239 54506 Vandoeuvre-les-Nancy, France bruno.scherrer@loria.fr Abs... | 2008 | 21 |
3,465 | Transfer Learning by Distribution Matching for Targeted Advertising Steffen Bickel, Christoph Sawade, and Tobias Scheffer University of Potsdam, Germany {bickel, sawade, scheffer}@cs.uni-potsdam.de Abstract We address the problem of learning classifiers for several related tasks that may differ in their jo... | 2008 | 210 |
3,466 | A Convergent O(n) Algorithm for Off-policy Temporal-difference Learning with Linear Function Approximation Richard S. Sutton, Csaba Szepesv´ari∗, Hamid Reza Maei Reinforcement Learning and Artificial Intelligence Laboratory Department of Computing Science University of Alberta Edmonton, Alberta, Canada T6G... | 2008 | 211 |
3,467 | Estimating Robust Query Models with Convex Optimization Kevyn Collins-Thompson∗ Microsoft Research 1 Microsoft Way Redmond, WA U.S.A. 98052 kevynct@microsoft.com Abstract Query expansion is a long-studied approach for improving retrieval effectiveness by enhancing the user’s original query with additi... | 2008 | 212 |
3,468 | Learning Taxonomies by Dependence Maximization Matthew B. Blaschko Arthur Gretton Max Planck Institute for Biological Cybernetics Spemannstr. 38 72076 T¨ubingen, Germany {blaschko,arthur}@tuebingen.mpg.de Abstract We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simult... | 2008 | 213 |
3,469 | Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets Jean-Philippe Pellet1,2 jep@zurich . ibm . com 1 Pattern Recognition and Machine Learning Group Swiss Federal Institute of Technology Zurich 8092 Zurich, Switzerland Abstract Andre Elisseeff2 ae l@ zurich... | 2008 | 214 |
3,470 | Goal-directed decision making in prefrontal cortex: A computational framework Matthew Botvinick James An Princeton Neuroscience Institute and Computer Science Department Department of Psychology, Princeton U... | 2008 | 215 |
3,471 | Localized Sliced Inverse Regression Qiang Wu, Sayan Mukherjee Department of Statistical Science Institute for Genome Sciences & Policy Department of Computer Science Duke University, Durham NC 27708-0251, U.S.A {qiang, sayan}@stat.duke.edu Feng Liang Department of Statistics University of Illinois a... | 2008 | 216 |
3,472 | Near-optimal Regret Bounds for Reinforcement Learning Peter Auer Thomas Jaksch Ronald Ortner University of Leoben, Franz-Josef-Strasse 18, 8700 Leoben, Austria {auer,tjaksch,rortner}@unileoben.ac.at Abstract For undiscounted reinforcement learning in Markov decision processes (MDPs) we consider the to... | 2008 | 217 |
3,473 | Non-parametric Regression Between Manifolds Florian Steinke1, Matthias Hein2 1 Max Planck Institute for Biological Cybernetics, 72076 T¨ubingen, Germany 2 Saarland University, 66041 Saarbr¨ucken, Germany steinke@tuebingen.mpg.de, hein@cs.uni-sb.de Abstract This paper discusses non-parametric regression betw... | 2008 | 218 |
3,474 | Unsupervised Learning of Visual Sense Models for Polysemous Words Kate Saenko MIT CSAIL Cambridge, MA saenko@csail.mit.edu Trevor Darrell UC Berkeley EECS / ICSI Berkeley, CA trevor@eecs.berkeley.edu Abstract Polysemy is a problem for methods that exploit image search engines to build object categ... | 2008 | 219 |
3,475 | Performance analysis for L2 kernel classification JooSeuk Kim Department of EECS University of Michigan Ann Arbor, MI, USA stannum@umich.edu Clayton D. Scott∗ Department of EECS University of Michigan Ann Arbor, MI, USA clayscot@umich.edu Abstract We provide statistical performance guarantees for... | 2008 | 22 |
3,476 | Extended Grassmann Kernels for Subspace-Based Learning Jihun Hamm GRASP Laboratory University of Pennsylvania Philadelphia, PA 19104 jhham@seas.upenn.edu Daniel D. Lee GRASP Laboratory University of Pennsylvania Philadelphia, PA 19104 ddlee@seas.upenn.edu Abstract Subspace-based learning probl... | 2008 | 220 |
3,477 | Implicit Mixtures of Restricted Boltzmann Machines Vinod Nair and Geoffrey Hinton Department of Computer Science, University of Toronto 10 King’s College Road, Toronto, M5S 3G5 Canada {vnair,hinton}@cs.toronto.edu Abstract We present a mixture model whose components are Restricted Boltzmann Machines (RBMs).... | 2008 | 221 |
3,478 | Self-organization using synaptic plasticity Vicenc¸ G´omez1 vgomez@iua.upf.edu Andreas Kaltenbrunner2 andreas.kaltenbrunner@upf.edu Hilbert J Kappen1 b.kappen@science.ru.nl Vicente L´opez2 vicente.lopez@barcelonamedia.org 1Department of Biophysics Radboud University Nijmegen 6525 EZ Nijmegen, The ... | 2008 | 222 |
3,479 | Interpreting the Neural Code with Formal Concept Analysis Dominik Endres, Peter F¨oldi´ak School of Psychology,University of St. Andrews KY16 9JP, UK {dme2,pf2}@st-andrews.ac.uk Abstract We propose a novel application of Formal Concept Analysis (FCA) to neural decoding: instead of just trying to figure out... | 2008 | 223 |
3,480 | Global Ranking Using Continuous Conditional Random Fields 1Tao Qin, 1Tie-Yan Liu, 2Xu-Dong Zhang, 2De-Sheng Wang, 1Hang Li 1Microsoft Research Asia, 2Tsinghua University 1{taoqin, tyliu, hangli}@microsoft.com 2{zhangxd, wangdsh ee}@tsinghua.edu.cn Abstract This paper studies global ranking problem by lear... | 2008 | 224 |
3,481 | Improving on Expectation Propagation Manfred Opper Computer Science, TU Berlin opperm@cs.tu-berlin.de Ulrich Paquet Computer Laboratory, University of Cambridge ulrich@cantab.net Ole Winther Informatics and Mathematical Modelling, Technical University of Denmark owi@imm.dtu.dk Abstract A series of... | 2008 | 225 |
3,482 | Learning a Discriminative Hidden Part Model for Human Action Recognition Yang Wang School of Computing Science Simon Fraser University Burnaby, BC, Canada, V5A 1S6 ywang12@cs.sfu.ca Greg Mori School of Computing Science Simon Fraser University Burnaby, BC, Canada, V5A 1S6 mori@cs.sfu.ca Abstract... | 2008 | 226 |
3,483 | Adaptive Template Matching with Shift-Invariant Semi-NMF Jonathan Le Roux Graduate School of Information Science and Technology The University of Tokyo leroux@hil.t.u-tokyo.ac.jp Alain de Cheveign´e CNRS, Universit´e Paris 5, and Ecole Normale Sup´erieure Alain.de.Cheveigne@ens.fr Lucas C. Parra∗ ... | 2008 | 227 |
3,484 | Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM Kentaro Katahira1,2, Jun Nishikawa2, Kazuo Okanoya2 and Masato Okada1,2 1Graduate School of Frontier Sciences The University of Tokyo Kashiwa, Chiba 277-8561, Japan 2RIKEN Brain Science Institute Wako, Saitama 351-01... | 2008 | 228 |
3,485 | Partially Observed Maximum Entropy Discrimination Markov Networks Jun Zhu† Eric P. Xing‡ Bo Zhang† †State Key Lab of Intelligent Tech & Sys, Tsinghua National TNList Lab, Dept. Comp Sci & Tech, †Tsinghua University, Beijing China. jun-zhu@mails.thu.edu.cn; dcszb@thu.edu.cn ‡School of Comp. Sci., Carnegie ... | 2008 | 229 |
3,486 | Influence of graph construction on graph-based clustering measures Markus Maier Ulrike von Luxburg Max Planck Institute for Biological Cybernetics, T¨ubingen, Germany Matthias Hein Saarland University, Saarbr¨ucken, Germany Abstract Graph clustering methods such as spectral clustering are defined for gene... | 2008 | 23 |
3,487 | Playing Pinball with non-invasive BCI Michael W. Tangermann Machine Learning Laboratory Berlin Institute of Technology Berlin, Germany schroedm@cs.tu-berlin.de Matthias Krauledat Machine Learning Laboratory Berlin Institute of Technology Berlin, Germany kraulem@cs.tu-berlin.de Konrad Grzeska Mac... | 2008 | 230 |
3,488 | Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction Shay B. Cohen Kevin Gimpel Noah A. Smith Language Technologies Institute School of Computer Science Carnegie Mellon University {scohen,kgimpel,nasmith}@cs.cmu.edu Abstract We explore a new Bayesian model for probabilistic gramma... | 2008 | 231 |
3,489 | Risk Bounds for Randomized Sample Compressed Classifiers Mohak Shah Centre for Intelligent Machines McGill University Montreal, QC, Canada, H3A 2A7 mohak@cim.mcgill.ca Abstract We derive risk bounds for the randomized classifiers in Sample Compression setting where the classifier-specification utilizes two ... | 2008 | 232 |
3,490 | Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text Yi Zhang Machine Learning Department Carnegie Mellon University yizhang1@cs.cmu.edu Jeff Schneider The Robotics Institute Carnegie Mellon University schneide@cs.cmu.edu Artur Dubrawski The Robotics Institute Carneg... | 2008 | 233 |
3,491 | Online Optimization in X-Armed Bandits S´ebastien Bubeck INRIA Lille, SequeL project, France sebastien.bubeck@inria.fr R´emi Munos INRIA Lille, SequeL project, France remi.munos@inria.fr Gilles Stoltz Ecole Normale Sup´erieure and HEC Paris gilles.stoltz@ens.fr Csaba Szepesv´ari Department of Comp... | 2008 | 234 |
3,492 | Variational Mixture of Gaussian Process Experts Chao Yuan and Claus Neubauer Siemens Corporate Research Integrated Data Systems Department 755 College Road East, Princeton, NJ 08540 {chao.yuan,claus.neubauer}@siemens.com Abstract Mixture of Gaussian processes models extended a single Gaussian process with... | 2008 | 235 |
3,493 | On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost Hamed Masnadi-Shirazi Statistical Visual Computing Laboratory, University of California, San Diego La Jolla, CA 92039 hmasnadi@ucsd.edu Nuno Vasconcelos Statistical Visual Computing Laboratory, Universit... | 2008 | 236 |
3,494 | Non-stationary dynamic Bayesian networks Joshua W. Robinson and Alexander J. Hartemink Department of Computer Science Duke University Durham, NC 27708-0129 {josh,amink}@cs.duke.edu Abstract A principled mechanism for identifying conditional dependencies in time-series data is provided through structure ... | 2008 | 237 |
3,495 | Nonlinear causal discovery with additive noise models Patrik O. Hoyer University of Helsinki Finland Dominik Janzing MPI for Biological Cybernetics T¨ubingen, Germany Joris Mooij MPI for Biological Cybernetics T¨ubingen, Germany Jonas Peters MPI for Biological Cybernetics T¨ubingen, Germany Be... | 2008 | 238 |
3,496 | Simple Local Models for Complex Dynamical Systems Erik Talvitie Computer Science and Engineering University of Michigan etalviti@umich.edu Satinder Singh Computer Science and Engineering University of Michigan baveja@umich.edu Abstract We present a novel mathematical formalism for the idea of a “loc... | 2008 | 239 |
3,497 | MDPs with Non-Deterministic Policies Mahdi Milani Fard School of Computer Science McGill University Montreal, Canada mmilan1@cs.mcgill.ca Joelle Pineau School of Computer Science McGill University Montreal, Canada jpineau@cs.mcgill.ca Abstract Markov Decision Processes (MDPs) have been extensive... | 2008 | 24 |
3,498 | Fitted Q-iteration by Advantage Weighted Regression Gerhard Neumann Institute for Theoretical Computer Science Graz University of Technology A-8010 Graz, Austria gerhard@igi.tu-graz.ac.at Jan Peters Max Planck Institute for Biological Cybernetics D-72076 Tübingen, Germany mail@jan-peters.net Abstrac... | 2008 | 240 |
3,499 | On the Generalization Ability of Online Strongly Convex Programming Algorithms Sham M. Kakade TTI Chicago Chicago, IL 60637 sham@tti-c.org Ambuj Tewari TTI Chicago Chicago, IL 60637 tewari@tti-c.org Abstract This paper examines the generalization properties of online convex programming algorithm... | 2008 | 241 |
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